The invention relates generally to Positron Emission Tomography (PET) systems, and more particularly, to methods and systems for performing overlap correction of 3D PET data reconstructed with fully iterative 3D algorithms.
In a PET system, an image of an object of interest is reconstructed from a plurality of partial emission projection data sets. This is achieved by acquiring projection data on a frame basis, with each acquired frame covering a specific axial field of view (FOV). Typically, each frame is acquired for a specific duration, for example three minutes, and the table is then moved to acquire the next frame. However, in this method the sensitivity of the end slices of a frame may be less than the sensitivity of the center slices. As a result, the end slices of each frame have poorer image quality than the center slices. To overcome this limitation, the acquired frames are typically overlapped from one table position to the next.
Different approaches may be followed for merging overlapped 2D and 3D PET data. When PET data is acquired in 2D acquisition mode, a collimator is used to restrict data that is not perpendicular in the axial direction of the patient. Thus, in 2D acquisition mode, each measured data point represents a single axial slice of the patient and is referred to as a sinogram rather than a projection plane. When data is acquired in this mode, a single projection slice of one frame corresponds to the identical location of projection measurement of an adjacent overlapped frame. Because the data from both frames represents the same physical location, data can be combined in projection space to improve the statistics of the measurement. The PET data in the overlapped region is then combined to generate a consolidated image. A common method used for image consolidation is taking a weighted average of the corresponding sinogram data from the two frames.
An alternate approach that is followed is to combine the images after the projection data has been reconstructed. Image reconstruction may be defined as a method to generate an image from the emission projection data. The emission data represents the integral of radioactive tracer values across a straight line through the body of the patient. This emission data is transformed to an image plane during reconstruction. An image plane is a matrix representation of tracer activity within an x-y plane of the body. Further, an image volume represents several image planes along the z-axis of the body.
PET data is also acquired in fully 3D acquisition mode. In this mode, a collimator is not used to isolate events from a single perpendicular axial slice. Instead, data from all available axial angles is acquired into a 3D projection plane. Each 3D projection plane consists of a set of 2D sinograms acquired at multiple axial angles and displacements. In 2D acquisition, sinogram lines of response through the overlapped regions do not pass through non-overlapped regions. The separability between the overlapped regions and non-overlapped regions permit the addition of the sinograms for the overlapped regions from the two frames. In a 3D acquisition, certain lines of response pass through both the overlapped region and non-overlapped regions. This makes the addition of projection data from multiple frames more complex.
A common method of reconstructing 3D PET projection plane data is to use Fourier Rebinning to convert the data to a stack of 2D sinograms. Once the data has been converted to 2D sinograms, the sinograms may be combined prior to reconstruction as in a 2D acquisition. When Fourier Rebinning is not used, 3D projection data is difficult to combine prior to reconstruction. In these instances, 3D data is typically combined after image reconstruction. However, combining data after image reconstruction reduces the available statistics for the image estimation portion of the process and may result in suboptimal image quality.